AIMC Topic: Humans

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A Federated Learning System for Histopathology Image Analysis With an Orchestral Stain-Normalization GAN.

IEEE transactions on medical imaging
Currently, data-driven based machine learning is considered one of the best choices in clinical pathology analysis, and its success is subject to the sufficiency of digitized slides, particularly those with deep annotations. Although centralized trai...

Federated Learning of Generative Image Priors for MRI Reconstruction.

IEEE transactions on medical imaging
Multi-institutional efforts can facilitate training of deep MRI reconstruction models, albeit privacy risks arise during cross-site sharing of imaging data. Federated learning (FL) has recently been introduced to address privacy concerns by enabling ...

Multi-Task Distributed Learning Using Vision Transformer With Random Patch Permutation.

IEEE transactions on medical imaging
The widespread application of artificial intelligence in health research is currently hampered by limitations in data availability. Distributed learning methods such as federated learning (FL) and split learning (SL) are introduced to solve this prob...

Federated Learning With Privacy-Preserving Ensemble Attention Distillation.

IEEE transactions on medical imaging
Federated Learning (FL) is a machine learning paradigm where many local nodes collaboratively train a central model while keeping the training data decentralized. This is particularly relevant for clinical applications since patient data are usually ...

FedNI: Federated Graph Learning With Network Inpainting for Population-Based Disease Prediction.

IEEE transactions on medical imaging
Graph Convolutional Neural Networks (GCNs) are widely used for graph analysis. Specifically, in medical applications, GCNs can be used for disease prediction on a population graph, where graph nodes represent individuals and edges represent individua...

Efficient Self-Attention Model for Speech Recognition-Based Assistive Robots Control.

Sensors (Basel, Switzerland)
Assistive robots are tools that people living with upper body disabilities can leverage to autonomously perform Activities of Daily Living (ADL). Unfortunately, conventional control methods still rely on low-dimensional, easy-to-implement interfaces ...

Artificial Intelligence-Assisted Diagnostic Cytology and Genomic Testing for Hematologic Disorders.

Cells
Artificial intelligence (AI) is a rapidly evolving field of computer science that involves the development of computational programs that can mimic human intelligence. In particular, machine learning and deep learning models have enabled the identifi...

Reliability of Medical Information Provided by ChatGPT: Assessment Against Clinical Guidelines and Patient Information Quality Instrument.

Journal of medical Internet research
BACKGROUND: ChatGPT-4 is the latest release of a novel artificial intelligence (AI) chatbot able to answer freely formulated and complex questions. In the near future, ChatGPT could become the new standard for health care professionals and patients t...

Exploring Language Used in Posts on r/birthcontrol: Case Study Using Data From Reddit Posts and Natural Language Processing to Advance Contraception Research.

Journal of medical Internet research
BACKGROUND: Contraceptive choice is central to reproductive autonomy. The internet, including social networking sites like Reddit, is an important resource for people seeking contraceptive information and support. A subreddit dedicated to contracepti...

Deep learning enhanced ultra-fast SPECT/CT bone scan in patients with suspected malignancy: quantitative assessment and clinical performance.

Physics in medicine and biology
. To evaluate the clinical performance of deep learning-enhanced ultrafast single photon emission computed tomography/computed tomography (SPECT/CT) bone scans in patients with suspected malignancy.. In this prospective study, 102 patients with poten...